Archaea in particle-rich waters of the Beaufort Shelf and Franklin Bay, Canadian Arctic: Clues to an allochthonous origin?
Bibliographic record
Abstract
We used 4',6-diamidino-2-phenylindole (DAPI) staining and fluorescent in situ hybridization to examine total bacterioplankton and archaeal distributions in surface waters and in deeper nepheloid layers and particle-poor waters across the Beaufort Shelf of the Canadian Arctic, including the Mackenzie River and Kugmallit Bay, as well as more distant Franklin Bay. Although the regional distribution of bacterioplankton was best explained by salinity (rs = -0.89, n = 28, p < 0.001) and indicators of primary production (chlorophyll a [Chl a], total organic carbon, and the ratio of Chl a to particulate organic carbon [Chl a: POC]), that of Archaea instead reflected measures of particulate matter, specifically microscopically determined particle concentration (rs = 0.85, n = 30, p < 0.001), suspended particulate matter, POC, particulate organic nitrogen (PON), and the beam attenuation coefficient. Moreover, when compared with similarly deep particle-poor waters, nepheloid layers were significantly enriched in Archaea (median concentration of 6.00 x 104 mL-1 [15.5% of bacterioplankton] vs. 1.79 x 4 mL-1 [3.6%]; p < 0.05), but not total bacterioplankton. The relationship between Archaea and particles, the dominance of the Mackenzie River as the regional particle source, the detection of highest archaeal concentrations (11.5-14.4 x 4 mL-1) in the river, and the highly significant correlation (rs = 0.97, n = 12, p < 0.001) between Archaea in particle-rich waters and PON (the river providing the upper end member) suggest that many of these Archaea derive from the river.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".